On the Segregation of Genetically Modified, Conventional, and
Organic Products in European Agriculture:
A Multi-market Equilibrium Analysis
GianCarlo Moschini, Harun Bulut, and Luigi Cembalo
Working Paper 05-WP 411
October 2005
Center for Agricultural and Rural Development
Iowa State University
Ames, Iowa 50011-1070
www.card.iastate.edu
GianCarlo Moschini is a professor of economics and Pioneer Endowed Chair in Science and
Technology Policy, Harun Bulut is a post-doctoral fellow, and Luigi Cembalo was a visiting
scientist, all with the Department of Economics at Iowa State University. Moschini and Bulut
developed, calibrated and simulated the model and wrote the paper. Cembalo assembled the
data used in the calibration. The support of the U.S. Department of Agriculture, through a
National Research Initiative grant, is gratefully acknowledged.
This paper is available online on the CARD Web site: www.card.iastate.edu. Permission is
granted to reproduce this information with appropriate attribution to the authors.
Questions or comments about the contents of this paper should be directed to GianCarlo
Moschini, 583 Heady Hall, Iowa State University, Ames, IA 50011-1070; Ph: (515) 294-5761; Fax:
(515) 294-6336; E-mail:
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and the widespread consumer and public opposition that has hampered adoption in a number of
countries. Indeed, GM crop adoption has been confined to a limited number of countries (the
United States, Argentina, Brazil, Canada, and China accounted for 96% of total GM crop
cultivation in 2004). Elsewhere, GM crop adoption has been slowed or hampered by novel
regulation, apparently in response to the aforementioned vigorous public opposition (Sheldon,
2002).
Whereas some earlier studies have documented sizeable efficiency gains attributable to new GM
crops (Moschini, Lapan, and Sobolevsky, 2000; Falck-Zepeda, Traxler, and Nelson, 2000), it has
become clear that a major feature of this new technology deserves more careful scrutiny.
Specifically, a portion of consumers perceives food made from GM products as weakly inferior in
quality relative to traditional food. But the mere introduction of GM crops means that, to deliver
traditional GM-free food, additional costs must be incurred (relative to the pre-innovation
situation). This is because the commodity-based production, marketing, and processing system,
long relied upon by the food industry, is not suited to avoid the commingling of GM and non-GM
crops. To satisfy the demand for non-GM food, costly identity preservation (IP) and segregation
activities are required. Thus, the innovation process has, in this context, brought about a new
market failure, essentially an externality on the production of traditional food products (Lapan
and Moschini, 2004; Fulton and Giannakas, 2004).
The public concern about GM products has affected the regulatory process in the European Union
(EU), yielding a sweeping new framework that became operative in April 2004. The new system
is meant to foster food safety, protect the environment, and ensure consumers’ “right to know,”
and it is centred on the notions of labelling and traceability (European Union, 2004). Specifically,
2
the new EU regulations require that food and feed consisting of, or produced from, GM crops be
clearly labelled as such and envision a system that guarantees full traceability of GM food (and
feed) products put on the marketplace.
1
Mandatory labelling is to apply to food and feed produced
from GM crops, including food from GM products even when it does not contain protein or DNA
from the GM crop (e.g., beet sugar). The threshold for avoiding the GM label is quite stringent:

co-existence issue explicitly indicates the need to allow for three distinct products (conventional,
organic, and GM). Furthermore, while it has been shown that the welfare impact of GM
innovation is ambiguous, it is of interest to understand what market conditions lead to negative as
opposed to positive welfare effects. In the context of a larger model that accommodates the three
types of products singled out by the co-existence issue, such welfare effects are likely to depend
on the interdependence between markets. More specific attention to such multi-market effects is
warranted.
2
In this article we develop a modelling framework that extends previous work by considering the
introduction of GM products in a system where two differentiated products already exist:
“conventional” food and “quality-enhanced” food. In the empirical part of the paper, the latter is
identified with “organic” food. The notion of organic food refers to the products of regulated
production processes that essentially forego the use of a range of chemical inputs (fertilizers,
herbicides, and pesticides) that are widely used in conventional agriculture. What specifically can
be called “organic” is a matter of national regulation, and the EU has its own rules and standards.
3
In the EU, organic production accounts for about 3% of the utilized agricultural area (UAA). But
the EU recognizes that a large number of other food products can claim superior quality
attributes. The identification of these products in the marketplace is promoted by EU regulations
that established special labels known as PDO (Protected Designation of Origin), PGI (Protected
Geographical Indication), and TSG (Traditional Speciality Guaranteed).
4
Thus, although our
model, strictly speaking, identifies the pre-GM differentiated food with organic food, we hope
that the results that we derive can be interpreted more generally to pertain to the broader set of
quality products that Europeans claim as a distinguishing feature of their agriculture (Fishler,
2002).
2
As noted by a reviewer, a study that models GM adoption with organic and conventional products in a
vertically differentiated products context is Giannakas and Yiannaka (2003).

the model thus calibrated under various assumptions, we can then shed some light on both the
qualitative and quantitative potential effects of large-scale GM product adoption on European
agriculture.
A major issue in the GM policy debate concerns consumers’ attitudes toward these new products
(Boccaletti and Moro, 2000). In representing the demand side of the market, therefore, we allow
for the fact that the three food products are perceived as differentiated by consumers. But we also
want to capture some stylized facts about consumer preferences with respect to these goods.
5
Specifically, conventional food is deemed no worse than GM food—in the definition of Lapan
and Moschini (2004), GM food is a “weakly inferior” substitute for conventional food. It seems
that individual preferences are also quite heterogeneous with respect to our other product, organic
food. Whereas some consumers have a strong preference for organic food, often based on
perceived health, environmental, and animal-welfare considerations, other consumers may,
ceteris paribus, prefer conventional food based on other quality attributes (such as appearance,
integrity, and taste). Thus, in particular, the assumption that conventional food is weakly inferior
to organic food would seem untenable. Hence, we develop a demand framework whereby organic
and conventional food products are “horizontally differentiated” whereas GM and non-GM food
products are “vertically differentiated.” We submit that this novel approach, detailed in the
section to follow, captures in an effective way the main attributes of demand in our context.
As for the supply side, an essential facet of the co-existence issue relates to the adjustments in
production brought about by the innovation adoption, in particular with regard to the welfare of
farmers. Concerning the latter, in a purely competitive sector such as agriculture, returns to
producers must be associated with the presence of some fixed factors of production. Land being
the obvious such fixed factor, in our model we represent the entire agricultural sector and assume
that a given endowment of land can be used to produce two outputs before GM innovation
(conventional and organic products) and three outputs after GM innovation (conventional,
organic, and GM products). Furthermore, it is apparent that organic products command a sizeable
price premium over conventional ones, while organic production accounts for only a small share
of overall production. The modelling avenue that we postulate to account for such stylized facts is
that organic production requires an additional input in the form of farmer-supplied effort, and that

3. The model
Based on the foregoing, the demand, supply and equilibrium conditions of an agricultural and
food sector before and after GM innovation are specified as follows.
3.1. Demand
Because it is widely accepted that such features of food demand arise from a collection of
consumers that manifest widely differing attitudes towards organic and GM food, it is useful to
derive aggregate demand explicitly from the specification of individual consumer preferences. To
implement the notion of weakly inferior substitutes, we extend the vertical product differentiation
model with unit demand of Mussa and Rosen (1978) and Tirole (1988, chapter 7). In that setting,
one postulates a population of consumers with heterogeneous preferences concerning two goods
(in addition to the numéraire) but in which all consumers agree that one good is no worse than the
other, ceteris paribus. We generalize that framework by allowing one additional good, such that
the individual agent utility function is defined over four goods: conventional food
n
q
, organic
6
A final consideration worth noting is that the model we develop and solve is calibrated at the farm-gate
level. Accordingly, the demand functions that we consider must be interpreted as derived demands. In
addition to reflecting the nature of final EU consumer demand, such derived demands implicitly account
for the (net) excess demand for EU products originating from the export market. Thus, although the model
formally represents a closed economy sector, it is in fact consistent with an open economy setting.
7
food
b
q
, GM food
g
q
, and a composite good

Thus, conventional and organic foods are treated as imperfect substitutes but with no presumption
that one is uniformly better than the other for all consumers. On the other hand, to capture the fact
that GM food is assumed to be a weakly inferior substitute for the conventional food, we assume
that the distribution of the corresponding parameter satisfies
[0,1]


. In the foregoing
specification, each individual consumer will consume two goods: either organic and
conventional, or organic and GM, although the heterogeneity of consumers implies that, in
aggregate, all three food types may be consumed.
8
More specifically, the consumer will buy the GM good if and only if
g n
p p

 , whereas he or
she would buy the conventional food if
g n
p p

 .
9
So, let
n g
Q q q

  and let



( )
u q
is such that the consumer will buy some amount of one of the goods, and that
income is sufficiently high so that an interior solution holds.
9
The consumer is actually indifferent between the two varieties if the equality holds, but the technical
(and, in equilibrium, inconsequential) assumption here is that, under equality, the conventional food is
purchased.
8
as
( , )
b
U y u Q q
  . Then the optimality conditions for an interior solution are ( , )
Q b Q
u Q q p

and ( , )
b
q b b
u Q q p

, which yield the individual demand functions
( , )
Q Q b
d p p
and
( , )
b Q b
d p p


(2)
Individuals with
g n
p p

 will prefer the GM product and buy
1
( , )
g Q g b
q d p p


 ,
( , )
b b g b
q d p p

 , and
0
n
q

(3)
Market demand functions are obtained by integrating over all types. Thus,
 
0
, , ( , ) ( )
g n
p p

 
 
(6)
where
( )
F

denotes the distribution function of consumer types.
To find explicit demand functions we rely on a simple parameterization that generalizes the
constant-elasticity demand framework. Specifically, the utility function is written as
9
  
1
1
1
, ( )
1
b b
u Q q k Q q

 






 
 


d p p k p p
 
 
   
 
 
 
    
   (8)


 
(1 )
(1 )
1 (1 ) (1 )(1 )
( , ) ( ) (1 )
b Q b Q b
d p p k p p
 
  
   
 

  
    
   (9)
Finally, we need to make assumptions about the distribution of consumer types (i.e., the
parameter

). To this end, we wish to allow for a fraction of consumers to be indifferent between

is ( ) 1f
 
 
.
Given this and the individual demands in equations (8)-(9), evaluating the integrals in equations
(4)-(6), for the case
n g
p p
 , we obtain
 
, , ( , )(1 )
g
n n g b Q n b
n
p
D p p p d p p
p

 
 
 
 
(10)
10
Indeed, a good share of agricultural production is used as animal feed and, as noted by Brookes (2004),
such a demand is likely indifferent as to whether the feed is GM or not.
11
The parameter

may also capture stylized facts about consumers’ handling of label information

n
p
D p p p d p p d p p A p p
p
  
 
 
    
 
 
 
(12)
where
( , )
Q b
d p
 and
( , )
b b
d p
 are given by (8) and (9), and
 
 


1 (1 )
(1 )
, 1
1 (1 )
g

0
g
D

and the demands for conventional and
organic food reduce to


, , ( , )
n n g b Q n b
D p p p d p p
 (14)


, , ( , )
b n g b b n b
D p p p d p p
 (15)
where, again, the functions
( , )
Q b
d p
 and
( , )
b b
d p
 are as defined in (8) and (9). Note that the
demand structure for the new product is described in terms of the same underlying preference
parameters
( , , and )

(16)
where
n

is a parameter that can be interpreted as the reciprocal of yield, and
( )
n
c w
is an
increasing, linearly homogeneous, and concave function of prices. Note that this cost function is
dual to a production function with a fixed proportion between land and a function of the bundle of
market inputs (unrestricted substitutability between market inputs is thus allowed).
Production of organic food, on the other hand, is assumed to require three types of inputs: land,
market-supplied inputs, and farmer-supplied effort. Again we assume fixed proportions between
land, a function of the bundle of market supply inputs, and farmer-supplied effort measured in
some efficiency units. But for the latter we assume that the cost of drawing the required farmer-
supplied efforts into organic production are increasing at the margin. For instance, one can
imagine a population of potential organic farmers, each with its own reservation price to enter this
particular industry (the heterogeneity displaying different abilities for supplying the effort
required in organic food production). If
b
x
denotes the production of organic food, the
corresponding cost function is written as
( , , ) ( , )
b b
b b b
C x w x c w z
 
 

n
c w c

such that (for given

and
w
) conventional food production is a
12
constant marginal cost industry. Organic production, on the other hand, is assumed to be an
increasing cost industry: at the margin, expanding organic production requires additional farmer-
supplied inputs that are available only at increasing cost. To capture that, and still take all market
prices as given, we write
( , ) (1 )
b
c w z z c

  , where
0


is a parameter to be determined at
the calibration stage. More specifically, we normalize


0,1
z  (without loss of generality,
because units are arbitrary) so that we can interpret
z
as the fraction of land that is allocated to

on the
production of conventional food, and a unit segregation cost
b
s
on the production of organic
food.
13
The parameter
b
s
will also capture the policies of organic food classification by means of
the presence of a trace amount of GM food.
14
Furthermore, GM regulation may mandate an
additional unit cost
t
for the producers of GM food (i.e., the mandatory labelling and traceability
requirements envisioned by the EU). Thus, the introduction of GM products affects the
production costs of all three food products, and the post-innovation marginal production costs are
represented by
12
Note that this formulation is quite consistent with the existence of market power in the pricing of GM
seeds, as in existing related models (e.g., Moschini and Lapan, 1997; Lapan and Moschini, 2004; Fulton
and Giannakas, 2004), as long as innovators do not extract the entire efficiency gain, i.e., there is some
spillover to farmers of the gross benefits (as found by Moschini, Lapan, and Sobolevsky, 2000 and
Falck-Zepeda, Traxler, and Nelson, 2000). In other words, the cost reduction represented by the
parameter

is to be interpreted as capturing the underlying efficiency gain in production, due to the
innovation, net of the possibly noncompetitive pricing of the improved inputs. But for the rest of the

n n n
p c s

  
(21)
* * *
(1 )
b b b
p z c s
 
   
(22)
* *
g n
p c t
 
  
(23)
* * * *
( , , )
b
b n g b
D p p p x

(24)
* * * *
( , , )
n
b n g n
D p p p x

x x x p p p z

. The pre-innovation
equilibrium is a special case, obtained by dropping equations (23) and (26), by setting
0
n b
s s t
  
, and by constraining the price of the new product to
g
p
(the choke price, that is,
14
For example, the fact that the EU organic food classification envisions zero tolerance of GM product (as
is also the case in the United States) can be interpreted as increasing the value of
b
s
.
14
the price that would drive GM food demand to zero). The resulting conditions can then be solved
for the pre-innovation equilibrium values
* * * * * *
( , , , , , )
b n b n
x x p p z

.
15
4. Data and calibration
We present the data on the parameters of the model in Table 1, which refers to the year 2000.

c
) was calculated as the difference between the price of conventional food
and rent expense per unit of conventional food, as formulated in equation (21) (with
0
n
s

).
15
Again, note that we are assuming competitive conditions, apart from the possible market power in the
pricing of GM seeds that is implicit in our model (as noted in footnote 13). A reviewer suggested that
possible market power in the food and retail industries should also be considered. But given the focus of
this paper, such an undertaking is best left for future research.
15
Table 1. Parameters Implemented in the Baseline
Description Unit Values
Primary Data
T
V
Total value of production
b€ 248.5
b
V
Value of organic food production
b€ 2.79
L
Total UAA in the EU mha 130.3
b
L
Land allocated to organic food

n n n
L x


Reciprocal of yield, normal food
u/ha 1,941
b b b
x V p

Organic food production
bu
1.71
b b b
L x


Reciprocal of yield, organic food
u/ha 452
n n
c p

 
Unit cost of market input bundle
€/u
0.89
/
b
z L L

Fraction of land allocated to organic 0.029

price and 20% of the handler’s mark-up at maximum. Sobolevsky, Moschini, and Lapan (2005)
rely on Lin, Chambers, and Harwood (2000) and use segregation costs between 3.4% and 10.3%
of the average US producers’ price for soybeans. Based on the foregoing, in this study we took
16
the segregation cost to be 5% of the selling price in the baseline solution. Therefore, because the
pre-innovation price of conventional food is normalized to equal 1, the unit segregation costs
n
s
and
b
s
for conventional and organic products, respectively, are set to 0.05 euros in the baseline
scenario.
There seems to be widespread agreement that GM crops can provide substantial efficiency gains
relative to their conventional counterparts, although there is less agreement on the magnitude of
such gains (e.g., Moschini, Lapan, and Sobolevsky, 2000; Bullock and Nitsi, 2001; Marra,
Pardey, and Alston, 2002; Qaim and Zilberman, 2003; Qaim and Traxler, 2005). To be broadly
consistent with such studies, here we make the (perhaps conservative) assumption that the
introduction of GM technology yields a 2% reduction in average cost of GM food production. But
note that, as discussed in footnote 13, this figure is to be interpreted as representing the farm-level
cost saving net of the price mark-up typically associated with GM seeds (as implied by the market
power due to the proprietary nature of GM technology). Thus, in our baseline model we set
0.98


.
Labelling and traceability costs are implemented in the model by the parameter
t
. In the baseline
solution we assume



. We do so by ensuring that, given the other assumptions
detailed in the foregoing, the chosen parameters allow the model to replicate the observed prices
and quantities for the benchmark year 2000. Specifically, in the pre-innovation competitive
equilibrium (
0
b
s

), by using the data presented in Table 1 and given the unit rent
208.8


computed as described earlier, from equation (21) (with
0
n
s

) the production cost parameter
c
must satisfy
( ) 208.8
n n
p c

  . Next, given
208.8



( , , )
( , , )
T
b n g
T
T
b n g
D p p p
D p p p

  



  




(30)
It can be verified that in our demand structure we have
T
 

. Thus, the parameter

is a
measure of the elasticity of total food demand, which is known to be quite inelastic in developed
countries (Moschini, 1998; Gracia, Gil, and Angulo, 1998; Tiffin and Tiffin, 1999). But here we
also need to consider that in our model the demand is for EU-produced food (i.e., net of import

CS

. Agricultural producers’ welfare is also affected by the innovation. In particular,
our model admits two distinct components of what is usually referred to as producer surplus
change,
PS

: a change in the return to land and a change in the return to efforts for producers of
organic product.
Consider first consumer welfare. Denote the pre-innovation and post-innovation equilibrium
solutions with superscripts
0
i

and
1
i

, respectively, such that the pre- and post-equilibrium
prices are written as
0 0 0
, , )
(
n b g
p p p
and
1 1 1
, , )
(
n b g

2
0
( )
[ ( )]
2
i
z
i
i i i
b b b
b b
L z L c
R p MC z dz

 
  

(32)
where ( ) (1 )
i i i i
b b b
MC z z c s
 
   
. The other component of producer surplus is the return to
landowners at equilibria
{0,1}
i

, which satisfies

set equal to zero (i.e.,
0
t

). Although there are likely minimal costs involved in labelling GM
food per se, the record-keeping mandated by the traceability requirements on GM food are likely
more onerous. Still, the benchmark of zero labelling and traceability costs is of some interest,
especially if one wants to disentangle the effects of such activities from the actual segregation
costs necessary to supply consumers with what they perceive as the superior products
(conventional and organic food with IP), and therefore we begin our analysis with that
assumption. We perform sensitivity analysis regarding this parameter value later. The other
critical parameter is the segregation cost. In the baseline scenario we assume that conventional
food and organic food face the same segregation costs, following the introduction of GM
products, and thus (as per earlier discussion) we set
0.05
n b
s s  .
Results for the base scenario are reported in Table 2. With the introduction of GM food, the price
of GM food declines relative to the pre-innovation choke price (recall that there is no demand for
GM food for all
g n
p p

), and this new product displaces mainly the conventional product (the
production of which decreases by 30.7 %). To interpret these and subsequent results it helps to
note explicitly that the difference in equilibrium prices between conventional and GM products is
determined by the supply side of the model, specifically,
* *
(1 )
n g n

p
)
€/u 1.00 1.026 0.026 2.55
organic food (
b
p
)
€/u 1.63 1.584 -0.046 -2.83
GM food (
g
p
)
€/u >1.00 0.958 -0.055 -5.44
Producer prices
normal food (
n n
p s

)
€/u 1.00 0.976 -0.024 -2.45
organic food (
b b
p s

)
€/u 1.63 1.534 -0.096 -5.90
GM food (
g
p t


Consumer surplus
b€ — — -1.55 —
Aggregate welfare
b€ — — -7.73 —
Note: see Table 1 for the definition of units of measurement.
All producer prices decrease in the new equilibrium (which in turn accounts for the decrease in
unit rent value of land). As for welfare effects, returns to land of course decline, but the non-land
returns to organic food producers increase. Overall, however, the returns to land obviously
dominate, and producer surplus declines substantially. Consumer surplus also declines: given our
parameterized preferences, the decline in the price of GM and organic food is not enough to
compensate for the increase in conventional food price. Because both producers and consumers
lose in the aggregate, the introduction of GM food in the EU agro-food system unambiguously
decreases the total welfare by 7.7 billion euros. We should emphasize again that, unlike other
studies in this area, in our calculation we do not account for the ex post returns to innovators that
develop the GM crops.
16
16
One way to rationalize our procedure is to consider ex post returns to innovators as compensating, in
expectation, for the R&D investments that made the innovation possible.
21
To further illustrate and qualify the foregoing results of the baseline scenarios, in what follows we
carry out a sensitivity analysis, whereby the effects of changes in the value of some key
parameters are explored.
17
5.2. Effects of segregation cost for organic food
In the baseline solution we postulated that segregation costs for conventional and organic food are
equal, that is,
n b
s s


food leads to a lower equilibrium price for organic food, as expected, whereas the equilibrium
prices of other goods increase. The effect on the equilibrium quantity demanded is for organic
food to increase (relative to the benchmark) and for the other two products to decrease, although
the magnitude of these effects is somewhat small. Per-hectare rent remains higher than at the
17
In addition to what is reported in Tables 3 to 5, we also performed sensitivity analysis on the value of
the demand elasticity

. Although omitted here for space reasons, we can note that such sensitivity
22
baseline, which increases the cost of production so that prices for conventional and GM food are
higher compared to the baseline. Both components of producer surplus increase relative to the
baseline, whereas consumer surplus is actually lower than at the baseline (the additional decrease
in organic food price does not offset the small price increases in the other two products). Overall,
aggregate welfare is minimally improved (relative to the baseline). Doubling
b
s
has essentially
the opposite effect of halving it, and therefore the economic effects are qualitatively reversed
relative to the baseline.
Table 3. Sensitivity Analysis on Segregation Costs
Segregation costs
Variable
0
b
s

0
n
s

b
s B

2
n
s B

Consumer prices
normal food (
n
p
)
1.0044 1.0255 1.0262 1.0241 1.0141 1.0530
organic food (
b
p
)
1.6460 1.5839 1.5655 1.6211 1.6117 1.5463
GM food (
g
p
)
0.9865 0.9577 0.9584 0.9563 0.9713 0.9352
Producer prices
normal (
n n
p s

)
1.0044 0.9755 0.9762 0.9741 0.9891 0.9530


)
217.26 161.24 162.65 158.52 187.64 117.64
Total return to land 28.32 21.02 21.20 20.66 24.46 15.33
Profit of organic
producers
230.97 251.35 257.48 239.61 241.65 267.15
Producer surplus 28.55 21.27 21.46 20.90 24.70 15.60
Variation in
consumer surplus
0.03 -1.55 -1.69 -1.27 -0.61 -4.23
Variation in
aggregate welfare
1.13 -7.73 -7.69 -7.82 -3.37 -16.08
Legend: B = base value (see Table 1). See Table 2 for the units of measurement and for
the pre-innovation solution.
analysis results remain qualitatively similar to those of the baseline scenario.
23
5.3. Effects of the overall level of segregation costs
As discussed earlier, a wide range of segregation costs have been contemplated in previous
studies, and much uncertainty remains as to their actual level because large-scale segregation of
GM and non-GM products has not yet been attempted. The parameter value for segregation cost
used in the baseline reflects an average of values found in previous studies, but clearly it is of
interest to evaluate the model’s sensitivity to changes in the level of segregation cost. To that end,
here we maintain the baseline’s assumption that segregation costs for organic and conventional
products are the same (
n b
s s

), and consider the effects of doubling and halving their level. The